Genomics and proteomics: role in the management of multiple sclerosis
- Cite this article as:
- Kappos, L., Achtnichts, L., Dahlke, F. et al. J Neurol (2005) 252(Suppl 3): iii21. doi:10.1007/s00415-005-2013-3
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Epidemiological studies and neuro-imaging have provided important insights into the natural course and prognostic factors of multiple sclerosis (MS), but our ability to predict different courses of the disease, and especially its response to treatment, is still very limited. Pharmacogenetic, pharmacogenomic and proteomic studies aim to assess gene and protein function in disease and promise to help to fill this important gap in our knowledge. Such studies may increase our understanding of disease mechanisms and responses to therapeutic compounds. Large-scale transcriptional expression profiling can be performed using gene chip microarrays; this technology allows screening for differentially expressed genes without having well-defined underlying hypotheses (“discovery-driven research”). To complement the technique, real time reverse transcription and polymerase chain reaction (RT-PCR) can be used for more targeted profiling and provides quantitative data on pre-selected genes. However, to maximise their clinical utility, expression profiling results need to be combined with well-documented clinical and imaging data.
Two forthcoming studies will investigate the long-term effects of early treatment with interferon beta-1b (IFNβ) on the course of MS. The BENEFIT (BEtaseron®/Betaferon® in Newly Emerging MS for Initial Treatment) study will incorporate pharmacogenetic and pharmacogenomic analyses to determine the genetic elements controlling treatment response. BEST-PGx (Betaferon®/Betaseron® in Early relapsing-remitting MS Surveillance Trial—Pharmacogenomics) is an exploratory 2-year study that will investigate the value of RNA expression profiling and pharmacogenetics in predicting treatment response to IFNβ in patients with early relapsing MS. The main goal of BEST-PGx is the identification of differences in gene expression profiles of patients showing differential treatment responses. In addition, this study may reveal new information relevant to the mechanism of action of interferon treatment in MS and also to differences in the underlying pathology of the immune system. These data may help us approach the goal of a really “individualised therapy” with increased efficacy, reduced adverse drug reactions and more efficient use of healthcare resources.